Nonlinear Observation and Control of a Lightweight Robotic Manipulator Actuated by Shape Memory Alloy (SMA) Wires

Doctoral thesis (2019)

In the last decade, the industry of Unmanned Aerial Vehicles (UAV) has gone through immense growth and diversification. Nowadays, we find drone based applications in a wide range of industries, such as ... [more ▼]

In the last decade, the industry of Unmanned Aerial Vehicles (UAV) has gone through immense growth and diversification. Nowadays, we find drone based applications in a wide range of industries, such as infrastructure, agriculture, transport, among others. This phenomenon has generated an increasing interest in the field of aerial manipulation. The implementation of aerial manipulators in the UAV industry could generate a significant increase in possible applications. However, the restriction on the available payload is one of the main setbacks of this approach. The impossibility to equip UAVs with heavy dexterous industrial robotic arms has driven the interest in the development of lightweight manipulators suitable for these applications. In the pursuit of providing an alternative lightweight solution for the aerial manipulators, this thesis proposes a lightweight robotic arm actuated by Shape Memory Alloy (SMA) wires. Although SMA wires represent a great alternative to conventional actuators for lightweight applications, they also imply highly nonlinear dynamics, which makes them difficult to control. Seeking to present a solution for the challenging task of controlling SMA wires, this work investigates the implications and advantages of the implementation of state feedback control techniques. The final aim of this study is the experimental implementation of a state feedback control for position regulation of the proposed lightweight robotic arm. Firstly, a mathematical model based on a constitutive model of the SMA wire is developed and experimentally validated. This model describes the dynamics of the proposed lightweight robotic arm from a mechatronics perspective. The proposed robotic arm is tested with three output feedback controllers for angular position control, namely a PID, a Sliding Mode and an Adaptive Controller. The controllers are tested in a MATLAB simulation and finally implemented and experimentally tested in various different scenarios. Following, in order to perform the experimental implementation of a state feedback control technique, a state and unknown input observer is developed. First, a non-switching observable model with unknown input of the proposed robotic arm is derived from the model previously presented. This model takes the martensite fraction rate of the original model as an unknown input, making it possible to eliminate the switching terms in the model. Then, a state and unknown input observer is proposed. This observer is based on the Extended Kalman Filter (EKF) for state estimation and sliding mode approach for unknown input estimation. Sufficient conditions for stability and convergence are established. The observer is tested in a MATLAB simulation and experimentally validated in various different scenarios. Finally, a state feedback control technique is tested in simulation and experimentally implemented for angular position control of the proposed lightweight robotic arm. Specifically, continuous and discrete-time State-Dependent Riccati Equation (SDRE) control laws are derived and implemented. To conclude, a quantitative and qualitative comparative analysis between an output feedback control approach and the implemented state feedback control is carried out under multiple scenarios, including position regulation, position tracking and tracking with changing payloads. [less ▲]